A growing number of health systems are beginning to quantify returns on their AI investments, with some reporting more than $100 million in annual value.
Boston Children’s Hospital has reclaimed about 60,000 hours from AI-enabled workflows since partnering with OpenAI at the enterprise level, saving more than $7 million in redeployed labor. More than one-third of the health system’s employees now use AI daily, with applications spanning supply chain invoices, operating room scheduling and clinical decision support. The Boston-based pediatric health system has also used AI tools to diagnose more than 40 rare conditions that had previously gone unresolved.
Chicago-based CommonSpirit Health generated more than $100 million in value through AI and robotic process automation in fiscal year 2025, with 242 applications now live across its hospitals. The results include measurable reductions in sepsis mortality, imaging scan times cut by as much as 50% and $10 million generated by its Insightli AI assistant alone. CommonSpirit has also rejected 15 proposed AI use cases through its governance review process.
Philadelphia-based Penn Medicine is projecting $105 million in AI-related benefits by fiscal year 2028. The academic health system has seen a 20% productivity improvement among project managers following AI adoption and is deploying a radiation oncology contouring tool, among other clinical applications. Penn Medicine describes its approach as “innovation with guardrails” — a framing that echoes how CommonSpirit and other health systems with strong early results are discussing governance.
New York City-based Mount Sinai Health System is projecting a $50 million bottom-line impact from its AI portfolio this year, with more than a 3-to-1 return on investment as the health system scales the technology across clinical and operational workflows, according to Robbie Freeman, DNP, RN, chief digital transformation officer. Among the strongest examples of AI-driven ROI at the health system is pressure injury prevention.
Those results stand out because most health systems are not there yet. According to an April report from Qventus, while 42% of health systems report deploying AI across multiple use cases, interviews with more than 60 CIOs, chief AI officers and other senior IT leaders found that only 4% have achieved scaled AI implementation with measurable outcomes. Four out of five respondents said they have difficulty measuring AI ROI, and 39% reported lacking a clear process for benchmarking performance.
What separates the health systems posting real numbers from the majority still struggling to measure results appears to be less about which tools they chose and more about how they built the infrastructure around them — governance frameworks, defined measurement strategies and a willingness to say no.
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